In the course of conducting their everyday affairs (whether personal or business), people generally access their networks of contacts for referrals, information and/or advice. For example, when choosing a physician, one might check with friends or relatives about past experiences with certain doctors. When seeking a new employee, a potential employer will often check with colleagues to see whether they know of a suitable candidate. And, when investigating new investment opportunities, an investor may consult with professional advisors as to the prospects of the target company.
In each of these and many other examples, an individual's decisions are often made easier by the advice of trusted associates and friends, but often that individual finds he or she does not have an appropriate contact with the information needed to help with a problem or task. At such times, the individual may ask his or her contacts for leads to contacts in their own “human networks”. This presents a quandary for the person asked for a referral—namely, whether or not to reveal his or her contacts to the requestor. By making such revelations, the “connector” may compromise his or her network or expose one or more of his or her contacts to unwanted solicitations. By not making the referral, however, the connector may risk his or her association with the person seeking the referral. Whether or not to make the referral often depends upon the degree of trust that the connector has in the person seeking the referral and any past experiences in making such referrals to the target referee.
Even where the referral is ultimately made, there is no guarantee that the referee is going to be a suitable candidate for the original requestor's purpose. Thus, the requestor may be forced to track down a number of leads (many of which may be unsuitable) in the hope of finding a suitable target. This process is rather inefficient, usually because a) the requestor does not have enough information about the contacts of his or her contacts in order to determine which contacts to approach for referrals, and/or b) the requestor has failed to properly elucidate his or her requirements and/or because the requestor was not provided with sufficient information regarding the potential target to be able to eliminate him or her from further consideration. In other words, the profiles of the desired target and the resulting candidates were not sufficiently developed to meaningfully assist in the selection process.
Nevertheless, despite these shortcomings, human networks are central to most, if not all, value-creating activities and operate at multiple levels, including personal networks (the personal and professional contacts each of us has), organizational networks (links within and between organizations), and associations and interest groups (people attracted by common values, interests, and goals). Today, many individuals may also be regarded as existing online community members, members of organizational networks (independent consultants, alliances, partnerships, consortiums, associations) or employees of small to large companies. They engage in human development, organizational learning, training, management, brokering, marketing, sales, trade, research, and consulting activities, all of which depend, to some degree, on inter-human networks. Such individuals generally understand the value of computer networks as tools for sharing information, but presently these individuals have only limited access to tools that can give them an edge (e.g., a competitive advantage) to make better human network connections on the Internet.
Others have recognized some of these deficiencies and have proposed partial solutions. For example, U.S. Pat. No. 6,115,709 to Gilmour and Wang proposes a method of constructing a user knowledge profile, having distinct public and private portions with different access restrictions. In an automated knowledge management system, electronic documents (e.g., e-mail messages and the like) are collected and each is associated with a user, such as for example the author of the document. Further, confidence levels are assigned to content within these documents and such content may be potentially indicative of a knowledge base of the user. The content is then stored in either the public or private portion of the user's knowledge profile depending upon whether the confidence level exceeds, or falls below, a predetermined threshold level. The public portion of the user knowledge profile is freely accessible by third parties, whereas the private portion has restricted access. Individual users' knowledge profiles may then be accessed (according to public/private access control restrictions) to determine whether a user is an appropriate candidate for a task (e.g., receipt of an e-mail message).
A related U.S. Pat. No. 6,205,472, to Gilmour, describes a scheme for querying a user profile. Access begins with the public portion of a user's knowledge profile for each of a plurality of potential targets of the electronic document. A matching operation is performed between a document term within the electronic document and public knowledge terms within the public portion of each knowledge profile to identify a first set of targets for which a match exists between the document term and at least one public knowledge term. The first set of targets is published to the originator. Responsive to a second query from the originator, the private portion of a knowledge profile for each of the plurality of potential targets of the electronic document is accessed, the private portion of each knowledge profile including private knowledge terms indicative of a knowledge base of a potential target of the electronic document. A second matching operation between the document term within the electronic document and the private knowledge terms within the private portion of each knowledge profile is performed to identify a second set of targets for which a match exists between the document term and at least one private knowledge term. Each target of the second set of targets is then prompted for authorization to be published to the originator.
These two examples of prior schemes for leveraging human network characteristics (in this case a worker's prior access to information of interest in a current electronic document) show the benefit of using automated means to assist in decision-making processes regarding the use of such networks. However, these schemes do not assist in the forming of relationships or introductions among members of disparate human networks nor do they provide for the brokering function discussed above, which is critical to the exchange of social capital among individuals.
The above-cited patents are not the only examples of schemes that attempt to address the social networking needs of people. Other schemes, which generally fall into one or more of a few categories, also exist. Among these are access control systems which generally allow only intended users to have access to information. Such systems may make use of encryption schemes such as public/private key encryption schemes.
Other methods of access control include the following.                1. Simple access that is either open or closed. In such schemes, users who have access to the system can “see” everything. Those without access to the system can, of course, see nothing. Access to the system is most often implemented by issuing a password, and in more rigorous systems also by a means of authentication using encrypted certificates issued by trusted third-party certificate authorities.        2. Schemes wherein data is separated into public and private designations. In these systems, users can designate some data areas as public and others as private. If others request access to data stored in private areas, the system will deny the request. Or in other implementations, the system may ask the user that designated the data as being private in the first place to decide whether or not to permit the requested access.        3. In a variation of the above scheme, data areas may be designated as either “public” or “private” and individuals are given either public or private access rights. Anyone can see public data areas while only persons given private access rights can see both public and private areas. One organization that appears to have implemented a scheme that makes use of this access control model is PeopleStream, Inc.        4. Use of multiple access groups to which specific people and other groups are assigned. This is similar to (3) above, except the system allows many different kinds of groups to be defined and applied to different documents, directories, or fields. This type of system is best managed by a professional system administrator because it is quite tedious to administer. Users have to be assigned individually to multiple groups        5. Role-based access control. Access groups are defined not just by specific people but also by specific roles. Whoever currently has a specific role has the access rights assigned to that role. This system usually also requires a separate method to authenticate that a particular person has a particular role.        
In addition to access control schemes, other profiling systems do exist. Such systems (e.g., as deployed in Microsoft's Passport and Novell's DigitalMe) are mainly used as adjuncts to eCommerce technologies and provide some limited contact book updating capabilities. Also, so-called “expert finding” systems (e.g., as deployed by Abuzz Technologies, Inc., Tacit Knowledge Systems, Inc. and others) generally lack the sophisticated software agents needed for true social networking and provide only an enhanced resume finding service. In many of these services, access controls to personal information are limited and little or no verification of user information is provided. Referral networks services, such as those developed by PeopleStream, ContactMaps, Six Degrees and others, include only limited user profiles and verification capabilities.